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This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without(More)
This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without(More)
This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without(More)
In this paper, we present a novel approach to predict the histological diagnosis of colorectal lesions from high-magnification colonoscopy images by means of Pit Pattern analysis. Motivated by the shortcomings of discriminant classifier approaches, we present a generative model based strategy which is closely related to content-based image retrieval (CBIR)(More)
This paper describes an application of machine learning techniques and evolutionary algorithms to colon cancer diagnosis. We propose an automated classification system for endoscopical images, which is supposed to support physicians in making correct decisions. Classification is done according to the pit-pattern scheme, which defines two/six different(More)
The diagnosis of colorectal cancer is usually supported by a staging system, such as the Duke or TNM system. In this work we discuss computer-aided pit-pattern classification of surface structures observed during high-magnification colonoscopy in order to support dignity assessment of colonic polyps. This is considered a quite promising approach because it(More)
In this work we present a method for an automated classification of en-doscopic images according to the pit pattern classification scheme. Images taken during colonoscopy are transformed using an extended and rotation invariant version of the Local Binary Patterns operator (LBP). The result of the transforms is then used to extract polygons from the images.(More)
OBJECTIVE There is evidence of an interaction between psychological factors and activity of inflammatory bowel disease (IBD). We examined the influence of depressive mood and associated anxiety on the course of IBD over a period of 18 months in a cohort of patients after an episode of active disease. METHODS In this prospective, longitudinal,(More)
We assessed the functional and structural brain disturbances in Wilson's disease (WD) by evoked potentials (EPs) and magnetic resonance imaging (MRI). All the 25 neurologically symptomatic and 44% of the 16 asymptomatic patients, assessed by both EPs (n = 48) and imaging (n = 41), had at least 1 abnormality of either prolonged EP conduction times,(More)